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皇甫逸凡, 冉雨叶, 封硕, 李菁. 数据库中细菌与人源药物代谢酶的比较及肠道菌群对药物代谢影响的展望[J]. 中国药科大学学报, 2023, 54(1): 122-130. DOI: 10.11665/j.issn.1000-5048.20220705001
引用本文: 皇甫逸凡, 冉雨叶, 封硕, 李菁. 数据库中细菌与人源药物代谢酶的比较及肠道菌群对药物代谢影响的展望[J]. 中国药科大学学报, 2023, 54(1): 122-130. DOI: 10.11665/j.issn.1000-5048.20220705001
HUANGFU Yifan, RAN Yuye, FENG Shuo, LI Jing. Comparison of bacterial and human drug metabolizing enzymes in database and prospect of influence of intestinal bacteria on drug metabolism[J]. Journal of China Pharmaceutical University, 2023, 54(1): 122-130. DOI: 10.11665/j.issn.1000-5048.20220705001
Citation: HUANGFU Yifan, RAN Yuye, FENG Shuo, LI Jing. Comparison of bacterial and human drug metabolizing enzymes in database and prospect of influence of intestinal bacteria on drug metabolism[J]. Journal of China Pharmaceutical University, 2023, 54(1): 122-130. DOI: 10.11665/j.issn.1000-5048.20220705001

数据库中细菌与人源药物代谢酶的比较及肠道菌群对药物代谢影响的展望

Comparison of bacterial and human drug metabolizing enzymes in database and prospect of influence of intestinal bacteria on drug metabolism

  • 摘要: 聚焦药物代谢相关的各种数据库和文献,对细菌来源与人源药物代谢酶的相关信息进行整理与分析,比较数据库中细菌与人源药物代谢酶收录信息的异同。结果发现细菌来源药物代谢酶比人源药物代谢酶要多很多(9 703 vs 964),但是细菌来源药物代谢酶的数量相较于BRENDA数据库中细菌酶的总体数量却少很多(9 703 vs 20 835 235)。这说明细菌对药物代谢的影响可能被大大地低估,需要进行深入的系统性研究。本文总结了目前研究肠道菌群影响药物代谢的进展及不足,提出研究思路,即通过人工智能对肠道细菌来源蛋白是否具有药物代谢的能力进行预测,用基因编辑与体内外实验等方法进行生物学功能的验证,并建立注释功能完善的肠道菌群与药物代谢相关数据库,为如何深入挖掘肠道菌群对药物代谢影响的研究提供坚实的理论基础。

     

    Abstract: This study focused on various databases and literatures related to drug metabolism, collated and analyzed the information related to bacterial and human drug metabolic enzymes, and compared the similarities and differences between the information included in the database of bacterial and human drug metabolic enzymes. Results found more bacterial drug metabolic enzymes than human drug metabolic enzymes (9 703 vs 964), but much less than the total number of bacterial enzymes in BRENDA database (9 703 vs 20 835 235), indicating that the influence of bacteria on drug metabolism could have been greatly underestimated, and that further systematic research is needed.We summarized the progress and shortcomings of the current research on the influence of intestinal flora on drug metabolism, and proposed a research idea, that is, to predict through artificial intelligence whether intestinal bacterial proteins have the ability to metabolize drugs, to verify their biological functions by in vitro/in vivo experiments and gene editing, and to establish a database of drug metabolic enzymes from intestinal bacteria with complete annotation functions, in an attempt to provide a solid theoretical basis for further exploration of the effects of intestinal flora on drug metabolism.

     

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